boston fire eda
Laura Evans
April 8, 2017
data.raw <- read_excel('february.2017-fireincidents.xlsx')## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [138, 19]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [185, 21]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [292, 21]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [377, 21]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [570, 19]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [634, 19]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1049, 19]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1582, 19]: expecting numeric: got 'N'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1689, 19]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1804, 21]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1818, 19]: expecting numeric: got 'N'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1878, 21]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1914, 19]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [1952, 19]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2218, 19]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2244, 21]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2304, 19]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2634, 19]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2787, 21]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [2889, 21]: expecting numeric: got 'E'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [3195, 21]: expecting numeric: got 'S'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [3249, 21]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [3258, 21]: expecting numeric: got 'W'## Warning in read_xlsx_(path, sheet, col_names = col_names, col_types =
## col_types, : [3271, 21]: expecting numeric: got 'E'str(data.raw)## Classes 'tbl_df', 'tbl' and 'data.frame': 3302 obs. of 24 variables:
## $ Incident Number : chr "17-0006578" "17-0006579" "17-0006580" "17-0006582" ...
## $ Exposure Number : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Alarm Date : chr "01-Feb-17" "01-Feb-17" "01-Feb-17" "01-Feb-17" ...
## $ Alarm Time : chr "00:44:33" "00:46:06" "01:12:34" "01:48:31" ...
## $ Incident Type : chr "745" "111" "651" "735" ...
## $ Incident Description : chr "Alarm system activation, no fire - unintentional" "Building fire" "Smoke scare, odor of smoke" "Alarm system sounded due to malfunction" ...
## $ Estimated Property Loss: num 0 2500 0 0 0 0 0 0 0 0 ...
## $ Estimated Content Loss : num 0 500 0 0 0 0 0 0 0 500 ...
## $ District : chr "01" "08" "09" "11" ...
## $ City Section : chr "EB" "MT" "JP" "BR" ...
## $ Neighborhood : chr "East Boston" "Mattapan" "Jamaica Plain" "Allston-Brighton" ...
## $ Zip : chr "02128" "02126" "02130" "02135" ...
## $ Property Use : chr "155" "419" "429" "429" ...
## $ Property Description : chr "Courthouse" "1 or 2 family dwelling" "Multifamily dwelling" "Multifamily dwelling" ...
## $ Street Number : chr "37" "371" "55" "20" ...
## $ Street Prefix : chr NA NA NA NA ...
## $ Street Name : chr "MERIDIAN" "RIVER" "ELIOT" "WASHINGTON" ...
## $ Street Type : chr "ST" "ST" "ST" "ST" ...
## $ Street Suffix : num NA NA NA NA NA NA NA NA NA NA ...
## $ Address 2 : chr ": #12-6153" NA NA ": #14-531" ...
## $ xStreet Prefix : num NA NA NA NA NA NA NA NA NA NA ...
## $ xStreet Name : chr NA NA NA NA ...
## $ xStreet Type : chr NA NA NA NA ...
## $ xStreet Suffix : num NA NA NA NA NA NA NA NA NA NA ...data.df <- data.raw
colnames(data.df) <- gsub('\\s', '.', colnames(data.df))
table(is.na(data.df$Street.Number))##
## FALSE TRUE
## 2927 375table(is.na(data.df$xStreet.Name))##
## FALSE TRUE
## 284 3018# so for these 375 you'll need to do address via cross street
table(data.df$Incident.Description)##
## Aircraft standby
## 4
## Alarm system activation, no fire - unintentional
## 163
## Alarm system sounded due to malfunction
## 92
## Animal problem
## 1
## Animal problem, Other
## 1
## Arcing, shorted electrical equipment
## 20
## Assist invalid
## 103
## Assist police or other governmental agency
## 40
## Attempt to burn
## 1
## BFD Drill
## 63
## Biological hazard investigation
## 1
## Biological hazard, confirmed or suspected
## 3
## Bomb scare - no bomb
## 2
## Breakdown of light ballast
## 1
## Brush or brush-and-grass mixture fire
## 6
## Building fire
## 28
## Carbon monoxide detector activation, no CO
## 18
## Carbon monoxide incident
## 29
## Central station, malicious false alarm
## 238
## Chemical hazard (no spill or leak)
## 4
## Chemical spill or leak
## 2
## Citizen complaint
## 2
## CO detector activation due to malfunction
## 37
## Combustible/flammable gas/liquid condition, other
## 1
## Cooking fire, confined to container
## 296
## Cover assignment, standby, moveup
## 4
## Defective elevator, no occupants
## 3
## Detector activation, no fire - unintentional
## 22
## Direct tie to FD, malicious false alarm
## 65
## Dispatched & cancelled en route
## 153
## Dumpster or other outside trash receptacle fire
## 5
## Electrical wiring/equipment problem, Other
## 34
## Extinguishing system activation
## 1
## False alarm or false call, Other
## 30
## Fire, Other
## 7
## FIU activity (not covered by other inc types)
## 4
## Fuel burner/boiler malfunction, fire confined
## 4
## Gas leak (natural gas or LPG)
## 51
## Gasoline or other flammable liquid spill
## 28
## Good intent call, Other
## 197
## Hazardous condition, Other
## 42
## HazMat release investigation w/no HazMat
## 5
## Heat detector activation due to malfunction
## 7
## Heat from short circuit (wiring), defective/worn
## 5
## Local alarm system, malicious false alarm
## 69
## Lock-out
## 56
## Malicious, mischievous false call, Other
## 13
## Mobile property (vehicle) fire, Other
## 2
## Municipal alarm system, malicious false alarm
## 40
## Natural vegetation fire, Other
## 3
## No Incident found on arrival at dispatch address
## 6
## Oil or other combustible liquid spill
## 29
## Outside equipment fire
## 5
## Outside rubbish fire, Other
## 11
## Outside rubbish, trash or waste fire
## 16
## Outside stationary compactor/compacted trash fire
## 2
## Overheated motor
## 12
## Overpressure rupture of steam boiler
## 2
## Passenger vehicle fire
## 17
## Person in distress, Other
## 9
## Police matter
## 48
## Power line down
## 15
## Public service
## 320
## Public service assistance, Other
## 24
## Rail vehicle fire
## 2
## Refrigeration leak
## 2
## Road freight or transport vehicle fire
## 2
## Service Call, other
## 63
## Severe weather or natural disaster, Other
## 5
## Smoke detector activation due to malfunction
## 43
## Smoke detector activation, no fire - unintentional
## 136
## Smoke from barbecue, tar kettle
## 9
## Smoke or odor removal
## 9
## Smoke scare, odor of smoke
## 57
## Special outside fire, Other
## 2
## Special type of incident, Other
## 149
## Sprinkler activation due to malfunction
## 18
## Sprinkler activation, no fire - unintentional
## 5
## Steam, Other gas mistaken for smoke, Other
## 6
## Steam, vapor, fog or dust thought to be smoke
## 65
## System malfunction, Other
## 21
## Telephone, malicious false alarm
## 5
## Trash or rubbish fire, contained
## 12
## Unintentional transmission of alarm, Other
## 30
## Vicinity alarm (incident in other location)
## 15
## Water evacuation
## 1
## Water or steam leak
## 96
## Water problem, Other
## 5
## Wrong location
## 22ggplot(data.df, aes(x=Incident.Description)) + geom_bar() +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
# worth rolling up or dropping some of these?
# or doing a deep dive into the most interesting/common?
data.df$Alarm.Date <- dmy(data.df$Alarm.Date)
data.df$day <- wday(data.df$Alarm.Date, label=TRUE)
ggplot(data.df, aes(x=day)) + geom_bar()
# norm for number of days in month? (but it's feb, so you don't need to)
data.df$hour <- hour(as.POSIXct( data.df$Alarm.Time, format='%H:%M:%S'))
ggplot(data.df, aes(x=hour)) + geom_bar()
# find types where the distro differs? small multiples?
ggplot(data.df, aes(x=Property.Description)) + geom_bar() +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
# TODO: drop some of the small ones here
data.df$full_street <- tolower(paste(data.df$Street.Name, data.df$Street.Type))
sam <- read.csv('Live_Street_Address_Management_SAM_Addresses.csv')
sam$FULL_STREET_NAME <- tolower(sam$FULL_STREET_NAME)
tmp1 <- sam[146057, ]
tmp2 <- data.df[1, c('Street.Number', 'full_street')]
# still getting doubles.... i think it's bc of dupes in the x/y in SAME
fire.locs <- merge(data.df, unique(sam[ ,c('X' ,'Y', 'STREET_NUMBER', 'FULL_STREET_NAME')]),
by.x=c('Street.Number', 'full_street'),
by.y=c('STREET_NUMBER', 'FULL_STREET_NAME'))
# so now we're short a few .... is it the ones with xstreets?
fire.locs <- ddply(fire.locs, colnames(fire.locs)[1:27], head, 1)
fire.locs <- ddply(fire.locs, c('Incident.Description'), mutate, descr.count=length(X) )
# fine tune this
map <- get_map(location = c(min(fire.locs$X), min(fire.locs$Y),
max(fire.locs$X), max(fire.locs$Y)))## Warning: bounding box given to google - spatial extent only approximate.## converting bounding box to center/zoom specification. (experimental)## Source : https://maps.googleapis.com/maps/api/staticmap?center=42.314435,-71.088306&zoom=12&size=640x640&scale=2&maptype=terrain&language=en-EN#map <- get_map(location = c(mean(fire.locs$X), mean(fire.locs$Y)), zoom = 12)
ggmap(map)
ggmap(map) + geom_point(data=fire.locs, aes(x=X, y=Y))
table(fire.locs$Incident.Description)##
## Aircraft standby
## 4
## Alarm system activation, no fire - unintentional
## 138
## Alarm system sounded due to malfunction
## 79
## Animal problem
## 1
## Animal problem, Other
## 1
## Arcing, shorted electrical equipment
## 14
## Assist invalid
## 99
## Assist police or other governmental agency
## 27
## BFD Drill
## 33
## Biological hazard, confirmed or suspected
## 2
## Bomb scare - no bomb
## 1
## Breakdown of light ballast
## 1
## Brush or brush-and-grass mixture fire
## 5
## Building fire
## 25
## Carbon monoxide detector activation, no CO
## 18
## Carbon monoxide incident
## 28
## Central station, malicious false alarm
## 216
## Chemical hazard (no spill or leak)
## 2
## Chemical spill or leak
## 1
## Citizen complaint
## 1
## CO detector activation due to malfunction
## 34
## Combustible/flammable gas/liquid condition, other
## 1
## Cooking fire, confined to container
## 261
## Defective elevator, no occupants
## 3
## Detector activation, no fire - unintentional
## 18
## Direct tie to FD, malicious false alarm
## 54
## Dispatched & cancelled en route
## 123
## Dumpster or other outside trash receptacle fire
## 5
## Electrical wiring/equipment problem, Other
## 21
## Extinguishing system activation
## 1
## False alarm or false call, Other
## 27
## Fire, Other
## 6
## FIU activity (not covered by other inc types)
## 4
## Fuel burner/boiler malfunction, fire confined
## 3
## Gas leak (natural gas or LPG)
## 40
## Gasoline or other flammable liquid spill
## 15
## Good intent call, Other
## 107
## Hazardous condition, Other
## 28
## HazMat release investigation w/no HazMat
## 4
## Heat detector activation due to malfunction
## 7
## Heat from short circuit (wiring), defective/worn
## 5
## Local alarm system, malicious false alarm
## 56
## Lock-out
## 43
## Malicious, mischievous false call, Other
## 12
## Mobile property (vehicle) fire, Other
## 1
## Municipal alarm system, malicious false alarm
## 2
## Natural vegetation fire, Other
## 1
## No Incident found on arrival at dispatch address
## 2
## Oil or other combustible liquid spill
## 11
## Outside equipment fire
## 2
## Outside rubbish fire, Other
## 9
## Outside rubbish, trash or waste fire
## 10
## Outside stationary compactor/compacted trash fire
## 1
## Overheated motor
## 7
## Overpressure rupture of steam boiler
## 2
## Passenger vehicle fire
## 14
## Person in distress, Other
## 8
## Police matter
## 34
## Power line down
## 6
## Public service
## 231
## Public service assistance, Other
## 19
## Rail vehicle fire
## 2
## Refrigeration leak
## 2
## Road freight or transport vehicle fire
## 1
## Service Call, other
## 39
## Severe weather or natural disaster, Other
## 2
## Smoke detector activation due to malfunction
## 40
## Smoke detector activation, no fire - unintentional
## 118
## Smoke from barbecue, tar kettle
## 3
## Smoke or odor removal
## 8
## Smoke scare, odor of smoke
## 43
## Special outside fire, Other
## 2
## Special type of incident, Other
## 107
## Sprinkler activation due to malfunction
## 16
## Sprinkler activation, no fire - unintentional
## 5
## Steam, Other gas mistaken for smoke, Other
## 6
## Steam, vapor, fog or dust thought to be smoke
## 47
## System malfunction, Other
## 19
## Telephone, malicious false alarm
## 5
## Trash or rubbish fire, contained
## 12
## Unintentional transmission of alarm, Other
## 28
## Vicinity alarm (incident in other location)
## 6
## Water evacuation
## 1
## Water or steam leak
## 85
## Water problem, Other
## 4
## Wrong location
## 14ggmap(map) + geom_point(data=fire.locs[fire.locs$descr.count>70, ],
aes(x=X, y=Y, color=Incident.Description))
incident.counts <- ddply(data.df, c('Incident.Description'), summarise, count=length(hour))
# unique this down somehow - sum the values and areas?
buildings <- read.csv('property-assessment-fy2017.csv')
buildings <- buildings[, c('PID', 'ST_NUM', 'ST_NAME', 'ST_NAME_SUF', 'UNIT_NUM',
'LU', 'OWN_OCC', 'AV_LAND', 'AV_BLDG', 'YR_BUILT',
'YR_REMOD', 'GROSS_AREA', 'LIVING_AREA', 'STRUCTURE_CLASS',
'R_OVRALL_CND')]
buildings.small <- ddply(buildings, c('ST_NUM', 'ST_NAME', 'ST_NAME_SUF',
'LU', 'YR_BUILT', 'YR_REMOD', 'STRUCTURE_CLASS',
'R_OVRALL_CND'), summarise, AV_LAND = sum(as.numeric(AV_LAND)),
AV_BLDG = sum(as.numeric(AV_BLDG)), GROSS_AREA=sum(GROSS_AREA),
LIVING_AREA=sum(LIVING_AREA))
buildings$full_street <- tolower(paste(buildings$ST_NAME, buildings$ST_NAME_SUF))
buildings$Street.Number <- gsub('\\s', '\\-', buildings$ST_NUM)
buildings.fires <- merge(buildings, data.df, by.x=c('Street.Number', 'full_street'),
by.y=c('Street.Number', 'full_street'), all.x =TRUE)
length(unique(buildings.fires$Incident.Number))## [1] 1091head(data.df$Incident.Number %in% unique(buildings.fires$Incident.Number), n=20)## [1] FALSE TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE FALSE
## [12] FALSE TRUE FALSE FALSE TRUE TRUE TRUE FALSE FALSE# where did the rest of my fires go?
# a lot of these fires are at addresses not in the assessment database and i don't know why
# lots of blanks in the st_num part of the assessment database
#otoh, are we duplicating a lot? - yes. fires in a multi-unit building get reported all of the units
table(buildings.fires$Incident.Number)##
## 17-0006579 17-0006580 17-0006582 17-0006584 17-0006586 17-0006587
## 1 5 1 1 4 1
## 17-0006590 17-0006594 17-0006598 17-0006599 17-0006601 17-0006607
## 1 1 1 5 1 1
## 17-0006622 17-0006624 17-0006633 17-0006645 17-0006648 17-0006653
## 1 228 1 1 1 5
## 17-0006659 17-0006669 17-0006674 17-0006677 17-0006681 17-0006686
## 1 6 1 1 1 1
## 17-0006688 17-0006689 17-0006693 17-0006712 17-0006721 17-0006727
## 1 1 1 1 1 1
## 17-0006741 17-0006744 17-0006745 17-0006748 17-0006750 17-0006751
## 1 3 1 1 1 1
## 17-0006762 17-0006764 17-0006767 17-0006768 17-0006777 17-0006781
## 280 1 1 4 1 1
## 17-0006787 17-0006789 17-0006795 17-0006796 17-0006803 17-0006811
## 1 1 1 1 1 1
## 17-0006813 17-0006815 17-0006819 17-0006841 17-0006865 17-0006867
## 1 1 1 1 2 1
## 17-0006872 17-0006874 17-0006875 17-0006879 17-0006889 17-0006895
## 1 1 8 2 2 1
## 17-0006900 17-0006902 17-0006909 17-0006910 17-0006935 17-0006936
## 2 1 1 2 1 1
## 17-0006964 17-0006972 17-0006974 17-0006993 17-0007000 17-0007015
## 2 2 1 1 1 33
## 17-0007019 17-0007025 17-0007028 17-0007030 17-0007031 17-0007034
## 1 1 1 1 1 1
## 17-0007035 17-0007043 17-0007044 17-0007048 17-0007058 17-0007076
## 1 1 1 1 1 1
## 17-0007081 17-0007084 17-0007090 17-0007091 17-0007105 17-0007107
## 4 1 1 1 1 1
## 17-0007117 17-0007120 17-0007124 17-0007126 17-0007129 17-0007131
## 2 1 1 1 1 1
## 17-0007134 17-0007135 17-0007144 17-0007147 17-0007160 17-0007176
## 2 1 1 1 1 1
## 17-0007178 17-0007180 17-0007193 17-0007197 17-0007215 17-0007219
## 1 1 1 1 1 1
## 17-0007222 17-0007232 17-0007238 17-0007243 17-0007244 17-0007248
## 11 1 10 1 1 1
## 17-0007249 17-0007269 17-0007270 17-0007277 17-0007278 17-0007281
## 1 6 1 1 79 6
## 17-0007282 17-0007284 17-0007299 17-0007306 17-0007310 17-0007317
## 1 3 1 1 24 9
## 17-0007325 17-0007328 17-0007329 17-0007333 17-0007334 17-0007339
## 1 1 4 92 1 1
## 17-0007344 17-0007355 17-0007364 17-0007367 17-0007368 17-0007370
## 1 3 1 1 19 1
## 17-0007379 17-0007382 17-0007385 17-0007392 17-0007393 17-0007394
## 1 1 1 1 1 1
## 17-0007408 17-0007412 17-0007413 17-0007414 17-0007420 17-0007429
## 3 2 1 1 16 1
## 17-0007455 17-0007462 17-0007471 17-0007474 17-0007475 17-0007488
## 1 1 1 2 1 1
## 17-0007489 17-0007495 17-0007499 17-0007500 17-0007506 17-0007509
## 1 1 1 1 1 2
## 17-0007524 17-0007540 17-0007547 17-0007552 17-0007558 17-0007562
## 1 1 4 1 1 1
## 17-0007564 17-0007569 17-0007571 17-0007576 17-0007581 17-0007585
## 3 1 7 1 108 1
## 17-0007590 17-0007605 17-0007607 17-0007611 17-0007628 17-0007629
## 1 4 4 1 2 132
## 17-0007631 17-0007637 17-0007639 17-0007641 17-0007645 17-0007647
## 1 4 1 2 1 1
## 17-0007648 17-0007652 17-0007659 17-0007663 17-0007664 17-0007676
## 22 1 1 1 18 1
## 17-0007692 17-0007693 17-0007698 17-0007707 17-0007720 17-0007727
## 2 2 5 26 1 1
## 17-0007735 17-0007737 17-0007741 17-0007747 17-0007749 17-0007755
## 1 1 1 5 14 2
## 17-0007764 17-0007773 17-0007777 17-0007794 17-0007798 17-0007800
## 1 1 1 1 1 1
## 17-0007803 17-0007804 17-0007806 17-0007815 17-0007827 17-0007833
## 1 1 1 1 1 1
## 17-0007843 17-0007849 17-0007857 17-0007863 17-0007870 17-0007871
## 1 1 1 2 1 6
## 17-0007872 17-0007875 17-0007877 17-0007889 17-0007891 17-0007897
## 1 1 1 4 1 1
## 17-0007902 17-0007903 17-0007916 17-0007917 17-0007922 17-0007927
## 3 1 3 1 1 1
## 17-0007928 17-0007961 17-0007965 17-0007977 17-0007979 17-0007982
## 1 1 3 1 1 1
## 17-0007993 17-0007998 17-0008001 17-0008005 17-0008020 17-0008021
## 1 4 1 8 1 1
## 17-0008029 17-0008031 17-0008037 17-0008039 17-0008041 17-0008042
## 1 1 1 1 284 26
## 17-0008045 17-0008052 17-0008054 17-0008055 17-0008058 17-0008060
## 1 2 8 4 4 1
## 17-0008078 17-0008095 17-0008099 17-0008103 17-0008105 17-0008107
## 1 1 1 2 1 1
## 17-0008117 17-0008118 17-0008121 17-0008129 17-0008142 17-0008149
## 1 24 1 1 6 1
## 17-0008153 17-0008154 17-0008158 17-0008159 17-0008205 17-0008223
## 1 47 35 1 17 1
## 17-0008239 17-0008257 17-0008267 17-0008269 17-0008276 17-0008277
## 1 1 1 1 1 9
## 17-0008289 17-0008291 17-0008293 17-0008299 17-0008306 17-0008309
## 4 1 1 1 8 1
## 17-0008319 17-0008321 17-0008326 17-0008329 17-0008330 17-0008333
## 17 1 1 1 1 1
## 17-0008353 17-0008354 17-0008358 17-0008364 17-0008379 17-0008380
## 7 7 228 3 1 1
## 17-0008386 17-0008392 17-0008412 17-0008429 17-0008434 17-0008447
## 1 2 6 4 1 13
## 17-0008449 17-0008451 17-0008458 17-0008467 17-0008471 17-0008492
## 1 1 1 1 1 1
## 17-0008494 17-0008495 17-0008500 17-0008503 17-0008513 17-0008514
## 1 1 3 1 1 1
## 17-0008521 17-0008536 17-0008545 17-0008546 17-0008553 17-0008558
## 1 1 1 1 2 6
## 17-0008561 17-0008562 17-0008566 17-0008571 17-0008572 17-0008574
## 1 2 89 1 1 1
## 17-0008580 17-0008581 17-0008584 17-0008585 17-0008586 17-0008588
## 4 1 4 1 3 1
## 17-0008593 17-0008600 17-0008604 17-0008612 17-0008617 17-0008618
## 2 1 1 1 4 1
## 17-0008619 17-0008621 17-0008623 17-0008626 17-0008629 17-0008632
## 1 16 1 1 1 1
## 17-0008633 17-0008635 17-0008638 17-0008639 17-0008643 17-0008645
## 1 1 18 16 1 1
## 17-0008649 17-0008660 17-0008666 17-0008668 17-0008674 17-0008675
## 5 7 2 1 1 1
## 17-0008677 17-0008681 17-0008684 17-0008686 17-0008692 17-0008697
## 1 1 1 1 1 3
## 17-0008698 17-0008700 17-0008709 17-0008716 17-0008728 17-0008731
## 1 1 1 1 1 1
## 17-0008732 17-0008734 17-0008736 17-0008737 17-0008752 17-0008755
## 1 6 2 1 1 1
## 17-0008757 17-0008761 17-0008763 17-0008764 17-0008765 17-0008766
## 1 1 1 1 1 1
## 17-0008768 17-0008769 17-0008776 17-0008779 17-0008780 17-0008796
## 5 1 1 1 1 1
## 17-0008799 17-0008812 17-0008813 17-0008816 17-0008819 17-0008841
## 1 1 1 228 2 1
## 17-0008844 17-0008845 17-0008869 17-0008872 17-0008881 17-0008882
## 1 102 1 23 1 1
## 17-0008884 17-0008902 17-0008906 17-0008907 17-0008913 17-0008915
## 4 1 1 1 3 1
## 17-0008916 17-0008922 17-0008927 17-0008930 17-0008943 17-0008945
## 3 1 55 1 1 1
## 17-0008947 17-0008950 17-0008961 17-0008962 17-0008966 17-0008968
## 2 1 1 2 4 1
## 17-0008969 17-0008975 17-0008978 17-0008980 17-0008988 17-0008990
## 1 1 2 1 1 1
## 17-0009013 17-0009015 17-0009016 17-0009021 17-0009022 17-0009024
## 9 5 1 62 1 1
## 17-0009029 17-0009034 17-0009045 17-0009046 17-0009047 17-0009054
## 2 1 3 1 1 16
## 17-0009061 17-0009062 17-0009066 17-0009068 17-0009070 17-0009072
## 1 2 1 1 1 1
## 17-0009076 17-0009085 17-0009093 17-0009097 17-0009101 17-0009106
## 1 26 1 1 1 1
## 17-0009107 17-0009108 17-0009111 17-0009118 17-0009119 17-0009121
## 1 1 1 1 1 7
## 17-0009123 17-0009129 17-0009131 17-0009143 17-0009145 17-0009156
## 2 1 1 1 1 3
## 17-0009162 17-0009170 17-0009172 17-0009178 17-0009192 17-0009201
## 1 7 1 10 84 1
## 17-0009202 17-0009214 17-0009223 17-0009230 17-0009237 17-0009241
## 1 1 1 1 1 1
## 17-0009245 17-0009246 17-0009249 17-0009256 17-0009271 17-0009284
## 1 1 4 1 1 1
## 17-0009286 17-0009287 17-0009289 17-0009297 17-0009299 17-0009312
## 1 1 1 1 1 1
## 17-0009319 17-0009325 17-0009328 17-0009336 17-0009345 17-0009353
## 1 89 1 1 1 26
## 17-0009357 17-0009359 17-0009382 17-0009387 17-0009388 17-0009395
## 5 1 1 1 1 1
## 17-0009396 17-0009409 17-0009422 17-0009424 17-0009427 17-0009439
## 1 1 1 1 24 2
## 17-0009440 17-0009450 17-0009452 17-0009455 17-0009460 17-0009474
## 1 1 1 1 1 1
## 17-0009494 17-0009503 17-0009504 17-0009528 17-0009531 17-0009537
## 1 1 1 1 11 1
## 17-0009546 17-0009551 17-0009552 17-0009561 17-0009564 17-0009571
## 55 1 1 1 1 1
## 17-0009591 17-0009595 17-0009604 17-0009605 17-0009608 17-0009618
## 3 1 1 1 1 1
## 17-0009622 17-0009637 17-0009639 17-0009652 17-0009653 17-0009655
## 1 1 15 1 6 1
## 17-0009661 17-0009689 17-0009699 17-0009719 17-0009724 17-0009730
## 1 1 2 1 1 1
## 17-0009733 17-0009744 17-0009752 17-0009757 17-0009760 17-0009763
## 1 6 1 17 1 2
## 17-0009770 17-0009778 17-0009787 17-0009788 17-0009801 17-0009802
## 1 1 1 81 1 2
## 17-0009805 17-0009807 17-0009809 17-0009813 17-0009814 17-0009818
## 2 1 3 1 1 1
## 17-0009819 17-0009833 17-0009858 17-0009873 17-0009889 17-0009890
## 1 1 1 5 1 1
## 17-0009891 17-0009898 17-0009899 17-0009900 17-0009902 17-0009910
## 1 1 5 1 1 1
## 17-0009913 17-0009920 17-0009927 17-0009928 17-0009929 17-0009937
## 1 1 1 1 1 1
## 17-0009944 17-0009945 17-0009954 17-0009955 17-0009974 17-0009975
## 1 1 1 1 1 2
## 17-0009979 17-0009985 17-0009986 17-0009998 17-0010005 17-0010019
## 1 5 4 1 1 1
## 17-0010020 17-0010027 17-0010028 17-0010031 17-0010036 17-0010044
## 20 3 1 1 1 1
## 17-0010046 17-0010049 17-0010051 17-0010053 17-0010067 17-0010092
## 1 1 1 1 1 1
## 17-0010097 17-0010104 17-0010109 17-0010112 17-0010117 17-0010119
## 1 1 1 1 1 3
## 17-0010131 17-0010133 17-0010137 17-0010158 17-0010161 17-0010166
## 1 1 1 1 1 11
## 17-0010190 17-0010192 17-0010195 17-0010196 17-0010200 17-0010204
## 3 1 1 1 1 1
## 17-0010208 17-0010224 17-0010225 17-0010229 17-0010231 17-0010233
## 3 1 1 4 3 2
## 17-0010238 17-0010241 17-0010243 17-0010246 17-0010248 17-0010254
## 1 1 1 11 2 1
## 17-0010257 17-0010266 17-0010267 17-0010272 17-0010276 17-0010278
## 2 1 1 1 171 1
## 17-0010293 17-0010294 17-0010297 17-0010302 17-0010314 17-0010317
## 2 1 280 1 2 2
## 17-0010323 17-0010325 17-0010328 17-0010341 17-0010343 17-0010346
## 2 1 14 2 11 1
## 17-0010356 17-0010357 17-0010361 17-0010369 17-0010371 17-0010405
## 1 1 1 2 2 13
## 17-0010406 17-0010409 17-0010419 17-0010420 17-0010424 17-0010432
## 1 2 1 2 1 1
## 17-0010433 17-0010440 17-0010443 17-0010450 17-0010455 17-0010457
## 13 1 5 1 1 1
## 17-0010464 17-0010465 17-0010469 17-0010474 17-0010478 17-0010483
## 1 24 2 1 1 1
## 17-0010485 17-0010489 17-0010491 17-0010496 17-0010499 17-0010504
## 5 1 40 40 1 1
## 17-0010507 17-0010509 17-0010511 17-0010513 17-0010514 17-0010515
## 1 1 4 1 23 1
## 17-0010520 17-0010530 17-0010546 17-0010547 17-0010555 17-0010560
## 1 1 1 24 1 1
## 17-0010567 17-0010573 17-0010596 17-0010606 17-0010611 17-0010625
## 1 24 1 1 2 1
## 17-0010630 17-0010632 17-0010635 17-0010638 17-0010639 17-0010646
## 92 41 11 1 1 1
## 17-0010664 17-0010667 17-0010669 17-0010671 17-0010676 17-0010690
## 1 29 1 1 1 1
## 17-0010698 17-0010721 17-0010731 17-0010736 17-0010741 17-0010756
## 1 1 1 1 2 2
## 17-0010762 17-0010764 17-0010765 17-0010769 17-0010781 17-0010794
## 1 1 3 1 1 1
## 17-0010798 17-0010803 17-0010805 17-0010812 17-0010814 17-0010826
## 2 1 1 2 2 1
## 17-0010831 17-0010839 17-0010841 17-0010842 17-0010846 17-0010847
## 3 1 1 1 1 1
## 17-0010849 17-0010850 17-0010864 17-0010870 17-0010882 17-0010883
## 1 1 1 4 1 1
## 17-0010888 17-0010892 17-0010893 17-0010896 17-0010902 17-0010917
## 1 1 1 1 1 2
## 17-0010921 17-0010922 17-0010936 17-0010939 17-0010941 17-0010942
## 1 1 2 1 1 1
## 17-0010947 17-0010950 17-0010951 17-0010953 17-0010954 17-0010965
## 1 1 1 1 67 1
## 17-0010967 17-0010968 17-0010971 17-0010974 17-0010977 17-0010982
## 38 1 2 102 1 1
## 17-0010984 17-0010986 17-0010987 17-0010993 17-0010994 17-0011002
## 1 1 1 5 1 1
## 17-0011006 17-0011015 17-0011016 17-0011019 17-0011021 17-0011024
## 1 1 1 1 1 1
## 17-0011028 17-0011030 17-0011031 17-0011033 17-0011034 17-0011042
## 1 1 1 1 1 4
## 17-0011051 17-0011058 17-0011063 17-0011070 17-0011079 17-0011085
## 38 1 5 1 1 1
## 17-0011088 17-0011089 17-0011090 17-0011093 17-0011094 17-0011103
## 1 2 1 3 1 1
## 17-0011106 17-0011111 17-0011112 17-0011114 17-0011115 17-0011120
## 1 1 7 1 1 1
## 17-0011133 17-0011145 17-0011147 17-0011151 17-0011152 17-0011155
## 2 14 2 1 7 2
## 17-0011156 17-0011167 17-0011172 17-0011186 17-0011188 17-0011191
## 1 1 5 1 1 4
## 17-0011196 17-0011201 17-0011202 17-0011204 17-0011210 17-0011213
## 1 1 1 1 1 1
## 17-0011215 17-0011218 17-0011230 17-0011232 17-0011234 17-0011238
## 1 3 1 1 1 3
## 17-0011242 17-0011246 17-0011247 17-0011250 17-0011255 17-0011257
## 1 1 1 2 7 2
## 17-0011258 17-0011261 17-0011293 17-0011294 17-0011295 17-0011298
## 1 1 1 3 1 1
## 17-0011304 17-0011312 17-0011314 17-0011320 17-0011325 17-0011326
## 1 1 1 4 1 2
## 17-0011333 17-0011346 17-0011354 17-0011359 17-0011363 17-0011365
## 1 1 4 1 1 1
## 17-0011368 17-0011378 17-0011388 17-0011399 17-0011405 17-0011407
## 1 4 1 14 1 1
## 17-0011416 17-0011428 17-0011430 17-0011433 17-0011435 17-0011443
## 1 1 14 1 1 1
## 17-0011454 17-0011465 17-0011467 17-0011469 17-0011476 17-0011479
## 1 1 1 2 1 1
## 17-0011486 17-0011487 17-0011491 17-0011497 17-0011499 17-0011502
## 1 1 1 1 2 4
## 17-0011504 17-0011506 17-0011510 17-0011514 17-0011520 17-0011522
## 1 1 3 1 1 1
## 17-0011523 17-0011526 17-0011527 17-0011531 17-0011533 17-0011538
## 1 1 1 1 5 1
## 17-0011541 17-0011554 17-0011555 17-0011556 17-0011572 17-0011573
## 1 1 79 1 1 1
## 17-0011574 17-0011579 17-0011583 17-0011585 17-0011592 17-0011594
## 1 1 2 1 1 1
## 17-0011606 17-0011608 17-0011609 17-0011613 17-0011619 17-0011621
## 31 4 1 7 1 1
## 17-0011624 17-0011647 17-0011652 17-0011658 17-0011670 17-0011675
## 1 1 1 1 1 1
## 17-0011681 17-0011691 17-0011694 17-0011696 17-0011705 17-0011711
## 129 1 4 1 1 1
## 17-0011716 17-0011719 17-0011722 17-0011725 17-0011730 17-0011731
## 3 3 1 1 1 1
## 17-0011736 17-0011737 17-0011740 17-0011744 17-0011754 17-0011755
## 1 2 1 14 4 102
## 17-0011774 17-0011784 17-0011786 17-0011787 17-0011791 17-0011814
## 75 1 1 1 1 2
## 17-0011816 17-0011817 17-0011819 17-0011822 17-0011823 17-0011825
## 4 1 1 1 1 1
## 17-0011829 17-0011835 17-0011839 17-0011846 17-0011855 17-0011858
## 1 1 203 1 3 1
## 17-0011863 17-0011864 17-0011881 17-0011882 17-0011900 17-0011902
## 28 1 1 3 1 2
## 17-0011912 17-0011918 17-0011919 17-0011931 17-0011937 17-0011938
## 1 1 1 1 1 1
## 17-0011940 17-0011962 17-0011970 17-0011971 17-0011972 17-0011981
## 1 1 4 1 1 1
## 17-0011984 17-0011995 17-0012008 17-0012015 17-0012017 17-0012020
## 1 1 1 4 1 1
## 17-0012031 17-0012033 17-0012034 17-0012036 17-0012039 17-0012048
## 1 1 1 1 1 4
## 17-0012051 17-0012060 17-0012064 17-0012071 17-0012078 17-0012083
## 1 1 1 1 1 1
## 17-0012092 17-0012094 17-0012100 17-0012102 17-0012104 17-0012106
## 1 1 1 1 20 5
## 17-0012114 17-0012116 17-0012125 17-0012128 17-0012129 17-0012130
## 1 1 1 1 1 6
## 17-0012131 17-0012134 17-0012137 17-0012138 17-0012143 17-0012146
## 1 3 1 1 17 10
## 17-0012151 17-0012152 17-0012161 17-0012164 17-0012174 17-0012179
## 79 1 1 19 1 1
## 17-0012184 17-0012185 17-0012188 17-0012194 17-0012207 17-0012213
## 14 1 1 14 1 1
## 17-0012217 17-0012220 17-0012229 17-0012240 17-0012249 17-0012267
## 1 25 5 6 1 1
## 17-0012268 17-0012301 17-0012306 17-0012327 17-0012329 17-0012338
## 1 1 1 1 1 1
## 17-0012358 17-0012364 17-0012371 17-0012379 17-0012391 17-0012396
## 1 1 1 1 1 1
## 17-0012408 17-0012416 17-0012417 17-0012423 17-0012429 17-0012430
## 47 6 1 1 129 1
## 17-0012435 17-0012437 17-0012441 17-0012447 17-0012448 17-0012457
## 1 1 1 1 2 1
## 17-0012459 17-0012460 17-0012466 17-0012477 17-0012479 17-0012487
## 5 1 1 132 1 1
## 17-0012492 17-0012494 17-0012506 17-0012514 17-0012517 17-0012540
## 1 2 1 1 1 1
## 17-0012551 17-0012561 17-0012562 17-0012563 17-0012567 17-0012574
## 79 5 3 1 1 1
## 17-0012578 17-0012579 17-0012584 17-0012588 17-0012593 17-0012599
## 1 1 4 13 1 1
## 17-0012600 17-0012601 17-0012617 17-0012622 17-0012627 17-0012632
## 1 1 1 1 6 1
## 17-0012639 17-0012640 17-0012647 17-0012659 17-0012662 17-0012668
## 2 1 2 1 1 1
## 17-0012692 17-0012693 17-0012696 17-0012705 17-0012760 17-0012767
## 1 1 1 1 1 5
## 17-0012773 17-0012780 17-0012781 17-0012787 17-0012788 17-0012797
## 4 1 2 3 1 1
## 17-0012805 17-0012815 17-0012817 17-0012818
## 1 1 1 1buildings.fires$fire <- ifelse(is.na(buildings.fires$Incident.Number), FALSE, TRUE)
ggplot(buildings.fires, aes(x=LU, fill=fire)) + geom_bar()
buildings.small$full_street <- tolower(paste(buildings.small$ST_NAME,
buildings.small$ST_NAME_SUF))
buildings.small$Street.Number <- gsub('\\s', '\\-', buildings.small$ST_NUM)
buildings.fires.small <- merge(buildings.small, data.df, by.x=c('Street.Number', 'full_street'),
by.y=c('Street.Number', 'full_street'), all.x =TRUE)
length(unique(buildings.fires.small$Incident.Number))## [1] 1091table(buildings.fires.small$Incident.Number)##
## 17-0006579 17-0006580 17-0006582 17-0006584 17-0006586 17-0006587
## 1 1 1 1 3 1
## 17-0006590 17-0006594 17-0006598 17-0006599 17-0006601 17-0006607
## 1 1 1 4 1 1
## 17-0006622 17-0006624 17-0006633 17-0006645 17-0006648 17-0006653
## 1 12 1 1 1 2
## 17-0006659 17-0006669 17-0006674 17-0006677 17-0006681 17-0006686
## 1 6 1 1 1 1
## 17-0006688 17-0006689 17-0006693 17-0006712 17-0006721 17-0006727
## 1 1 1 1 1 1
## 17-0006741 17-0006744 17-0006745 17-0006748 17-0006750 17-0006751
## 1 2 1 1 1 1
## 17-0006762 17-0006764 17-0006767 17-0006768 17-0006777 17-0006781
## 4 1 1 1 1 1
## 17-0006787 17-0006789 17-0006795 17-0006796 17-0006803 17-0006811
## 1 1 1 1 1 1
## 17-0006813 17-0006815 17-0006819 17-0006841 17-0006865 17-0006867
## 1 1 1 1 1 1
## 17-0006872 17-0006874 17-0006875 17-0006879 17-0006889 17-0006895
## 1 1 2 1 2 1
## 17-0006900 17-0006902 17-0006909 17-0006910 17-0006935 17-0006936
## 2 1 1 2 1 1
## 17-0006964 17-0006972 17-0006974 17-0006993 17-0007000 17-0007015
## 2 2 1 1 1 2
## 17-0007019 17-0007025 17-0007028 17-0007030 17-0007031 17-0007034
## 1 1 1 1 1 1
## 17-0007035 17-0007043 17-0007044 17-0007048 17-0007058 17-0007076
## 1 1 1 1 1 1
## 17-0007081 17-0007084 17-0007090 17-0007091 17-0007105 17-0007107
## 2 1 1 1 1 1
## 17-0007117 17-0007120 17-0007124 17-0007126 17-0007129 17-0007131
## 2 1 1 1 1 1
## 17-0007134 17-0007135 17-0007144 17-0007147 17-0007160 17-0007176
## 2 1 1 1 1 1
## 17-0007178 17-0007180 17-0007193 17-0007197 17-0007215 17-0007219
## 1 1 1 1 1 1
## 17-0007222 17-0007232 17-0007238 17-0007243 17-0007244 17-0007248
## 5 1 3 1 1 1
## 17-0007249 17-0007269 17-0007270 17-0007277 17-0007278 17-0007281
## 1 6 1 1 10 3
## 17-0007282 17-0007284 17-0007299 17-0007306 17-0007310 17-0007317
## 1 3 1 1 3 1
## 17-0007325 17-0007328 17-0007329 17-0007333 17-0007334 17-0007339
## 1 1 2 5 1 1
## 17-0007344 17-0007355 17-0007364 17-0007367 17-0007368 17-0007370
## 1 3 1 1 3 1
## 17-0007379 17-0007382 17-0007385 17-0007392 17-0007393 17-0007394
## 1 1 1 1 1 1
## 17-0007408 17-0007412 17-0007413 17-0007414 17-0007420 17-0007429
## 3 2 1 1 1 1
## 17-0007455 17-0007462 17-0007471 17-0007474 17-0007475 17-0007488
## 1 1 1 2 1 1
## 17-0007489 17-0007495 17-0007499 17-0007500 17-0007506 17-0007509
## 1 1 1 1 1 2
## 17-0007524 17-0007540 17-0007547 17-0007552 17-0007558 17-0007562
## 1 1 3 1 1 1
## 17-0007564 17-0007569 17-0007571 17-0007576 17-0007581 17-0007585
## 1 1 3 1 11 1
## 17-0007590 17-0007605 17-0007607 17-0007611 17-0007628 17-0007629
## 1 4 4 1 1 2
## 17-0007631 17-0007637 17-0007639 17-0007641 17-0007645 17-0007647
## 1 2 1 2 1 1
## 17-0007648 17-0007652 17-0007659 17-0007663 17-0007664 17-0007676
## 3 1 1 1 4 1
## 17-0007692 17-0007693 17-0007698 17-0007707 17-0007720 17-0007727
## 1 1 3 3 1 1
## 17-0007735 17-0007737 17-0007741 17-0007747 17-0007749 17-0007755
## 1 1 1 2 3 2
## 17-0007764 17-0007773 17-0007777 17-0007794 17-0007798 17-0007800
## 1 1 1 1 1 1
## 17-0007803 17-0007804 17-0007806 17-0007815 17-0007827 17-0007833
## 1 1 1 1 1 1
## 17-0007843 17-0007849 17-0007857 17-0007863 17-0007870 17-0007871
## 1 1 1 2 1 2
## 17-0007872 17-0007875 17-0007877 17-0007889 17-0007891 17-0007897
## 1 1 1 4 1 1
## 17-0007902 17-0007903 17-0007916 17-0007917 17-0007922 17-0007927
## 3 1 1 1 1 1
## 17-0007928 17-0007961 17-0007965 17-0007977 17-0007979 17-0007982
## 1 1 3 1 1 1
## 17-0007993 17-0007998 17-0008001 17-0008005 17-0008020 17-0008021
## 1 2 1 1 1 1
## 17-0008029 17-0008031 17-0008037 17-0008039 17-0008041 17-0008042
## 1 1 1 1 14 3
## 17-0008045 17-0008052 17-0008054 17-0008055 17-0008058 17-0008060
## 1 2 4 2 3 1
## 17-0008078 17-0008095 17-0008099 17-0008103 17-0008105 17-0008107
## 1 1 1 2 1 1
## 17-0008117 17-0008118 17-0008121 17-0008129 17-0008142 17-0008149
## 1 1 1 1 4 1
## 17-0008153 17-0008154 17-0008158 17-0008159 17-0008205 17-0008223
## 1 2 4 1 3 1
## 17-0008239 17-0008257 17-0008267 17-0008269 17-0008276 17-0008277
## 1 1 1 1 1 4
## 17-0008289 17-0008291 17-0008293 17-0008299 17-0008306 17-0008309
## 3 1 1 1 4 1
## 17-0008319 17-0008321 17-0008326 17-0008329 17-0008330 17-0008333
## 4 1 1 1 1 1
## 17-0008353 17-0008354 17-0008358 17-0008364 17-0008379 17-0008380
## 4 4 12 3 1 1
## 17-0008386 17-0008392 17-0008412 17-0008429 17-0008434 17-0008447
## 1 2 5 1 1 10
## 17-0008449 17-0008451 17-0008458 17-0008467 17-0008471 17-0008492
## 1 1 1 1 1 1
## 17-0008494 17-0008495 17-0008500 17-0008503 17-0008513 17-0008514
## 1 1 1 1 1 1
## 17-0008521 17-0008536 17-0008545 17-0008546 17-0008553 17-0008558
## 1 1 1 1 2 2
## 17-0008561 17-0008562 17-0008566 17-0008571 17-0008572 17-0008574
## 1 2 14 1 1 1
## 17-0008580 17-0008581 17-0008584 17-0008585 17-0008586 17-0008588
## 2 1 2 1 3 1
## 17-0008593 17-0008600 17-0008604 17-0008612 17-0008617 17-0008618
## 2 1 1 1 2 1
## 17-0008619 17-0008621 17-0008623 17-0008626 17-0008629 17-0008632
## 1 1 1 1 1 1
## 17-0008633 17-0008635 17-0008638 17-0008639 17-0008643 17-0008645
## 1 1 10 1 1 1
## 17-0008649 17-0008660 17-0008666 17-0008668 17-0008674 17-0008675
## 4 3 2 1 1 1
## 17-0008677 17-0008681 17-0008684 17-0008686 17-0008692 17-0008697
## 1 1 1 1 1 2
## 17-0008698 17-0008700 17-0008709 17-0008716 17-0008728 17-0008731
## 1 1 1 1 1 1
## 17-0008732 17-0008734 17-0008736 17-0008737 17-0008752 17-0008755
## 1 2 2 1 1 1
## 17-0008757 17-0008761 17-0008763 17-0008764 17-0008765 17-0008766
## 1 1 1 1 1 1
## 17-0008768 17-0008769 17-0008776 17-0008779 17-0008780 17-0008796
## 3 1 1 1 1 1
## 17-0008799 17-0008812 17-0008813 17-0008816 17-0008819 17-0008841
## 1 1 1 12 2 1
## 17-0008844 17-0008845 17-0008869 17-0008872 17-0008881 17-0008882
## 1 9 1 3 1 1
## 17-0008884 17-0008902 17-0008906 17-0008907 17-0008913 17-0008915
## 2 1 1 1 1 1
## 17-0008916 17-0008922 17-0008927 17-0008930 17-0008943 17-0008945
## 2 1 3 1 1 1
## 17-0008947 17-0008950 17-0008961 17-0008962 17-0008966 17-0008968
## 2 1 1 2 2 1
## 17-0008969 17-0008975 17-0008978 17-0008980 17-0008988 17-0008990
## 1 1 1 1 1 1
## 17-0009013 17-0009015 17-0009016 17-0009021 17-0009022 17-0009024
## 4 2 1 5 1 1
## 17-0009029 17-0009034 17-0009045 17-0009046 17-0009047 17-0009054
## 2 1 2 1 1 1
## 17-0009061 17-0009062 17-0009066 17-0009068 17-0009070 17-0009072
## 1 2 1 1 1 1
## 17-0009076 17-0009085 17-0009093 17-0009097 17-0009101 17-0009106
## 1 3 1 1 1 1
## 17-0009107 17-0009108 17-0009111 17-0009118 17-0009119 17-0009121
## 1 1 1 1 1 2
## 17-0009123 17-0009129 17-0009131 17-0009143 17-0009145 17-0009156
## 2 1 1 1 1 3
## 17-0009162 17-0009170 17-0009172 17-0009178 17-0009192 17-0009201
## 1 3 1 5 3 1
## 17-0009202 17-0009214 17-0009223 17-0009230 17-0009237 17-0009241
## 1 1 1 1 1 1
## 17-0009245 17-0009246 17-0009249 17-0009256 17-0009271 17-0009284
## 1 1 2 1 1 1
## 17-0009286 17-0009287 17-0009289 17-0009297 17-0009299 17-0009312
## 1 1 1 1 1 1
## 17-0009319 17-0009325 17-0009328 17-0009336 17-0009345 17-0009353
## 1 14 1 1 1 3
## 17-0009357 17-0009359 17-0009382 17-0009387 17-0009388 17-0009395
## 3 1 1 1 1 1
## 17-0009396 17-0009409 17-0009422 17-0009424 17-0009427 17-0009439
## 1 1 1 1 4 2
## 17-0009440 17-0009450 17-0009452 17-0009455 17-0009460 17-0009474
## 1 1 1 1 1 1
## 17-0009494 17-0009503 17-0009504 17-0009528 17-0009531 17-0009537
## 1 1 1 1 2 1
## 17-0009546 17-0009551 17-0009552 17-0009561 17-0009564 17-0009571
## 3 1 1 1 1 1
## 17-0009591 17-0009595 17-0009604 17-0009605 17-0009608 17-0009618
## 2 1 1 1 1 1
## 17-0009622 17-0009637 17-0009639 17-0009652 17-0009653 17-0009655
## 1 1 2 1 3 1
## 17-0009661 17-0009689 17-0009699 17-0009719 17-0009724 17-0009730
## 1 1 2 1 1 1
## 17-0009733 17-0009744 17-0009752 17-0009757 17-0009760 17-0009763
## 1 1 1 2 1 2
## 17-0009770 17-0009778 17-0009787 17-0009788 17-0009801 17-0009802
## 1 1 1 3 1 1
## 17-0009805 17-0009807 17-0009809 17-0009813 17-0009814 17-0009818
## 2 1 3 1 1 1
## 17-0009819 17-0009833 17-0009858 17-0009873 17-0009889 17-0009890
## 1 1 1 3 1 1
## 17-0009891 17-0009898 17-0009899 17-0009900 17-0009902 17-0009910
## 1 1 2 1 1 1
## 17-0009913 17-0009920 17-0009927 17-0009928 17-0009929 17-0009937
## 1 1 1 1 1 1
## 17-0009944 17-0009945 17-0009954 17-0009955 17-0009974 17-0009975
## 1 1 1 1 1 2
## 17-0009979 17-0009985 17-0009986 17-0009998 17-0010005 17-0010019
## 1 5 2 1 1 1
## 17-0010020 17-0010027 17-0010028 17-0010031 17-0010036 17-0010044
## 1 1 1 1 1 1
## 17-0010046 17-0010049 17-0010051 17-0010053 17-0010067 17-0010092
## 1 1 1 1 1 1
## 17-0010097 17-0010104 17-0010109 17-0010112 17-0010117 17-0010119
## 1 1 1 1 1 2
## 17-0010131 17-0010133 17-0010137 17-0010158 17-0010161 17-0010166
## 1 1 1 1 1 3
## 17-0010190 17-0010192 17-0010195 17-0010196 17-0010200 17-0010204
## 1 1 1 1 1 1
## 17-0010208 17-0010224 17-0010225 17-0010229 17-0010231 17-0010233
## 2 1 1 1 2 2
## 17-0010238 17-0010241 17-0010243 17-0010246 17-0010248 17-0010254
## 1 1 1 3 2 1
## 17-0010257 17-0010266 17-0010267 17-0010272 17-0010276 17-0010278
## 2 1 1 1 12 1
## 17-0010293 17-0010294 17-0010297 17-0010302 17-0010314 17-0010317
## 2 1 4 1 2 2
## 17-0010323 17-0010325 17-0010328 17-0010341 17-0010343 17-0010346
## 2 1 2 2 5 1
## 17-0010356 17-0010357 17-0010361 17-0010369 17-0010371 17-0010405
## 1 1 1 1 1 3
## 17-0010406 17-0010409 17-0010419 17-0010420 17-0010424 17-0010432
## 1 2 1 2 1 1
## 17-0010433 17-0010440 17-0010443 17-0010450 17-0010455 17-0010457
## 3 1 3 1 1 1
## 17-0010464 17-0010465 17-0010469 17-0010474 17-0010478 17-0010483
## 1 3 1 1 1 1
## 17-0010485 17-0010489 17-0010491 17-0010496 17-0010499 17-0010504
## 5 1 11 11 1 1
## 17-0010507 17-0010509 17-0010511 17-0010513 17-0010514 17-0010515
## 1 1 2 1 3 1
## 17-0010520 17-0010530 17-0010546 17-0010547 17-0010555 17-0010560
## 1 1 1 3 1 1
## 17-0010567 17-0010573 17-0010596 17-0010606 17-0010611 17-0010625
## 1 3 1 1 2 1
## 17-0010630 17-0010632 17-0010635 17-0010638 17-0010639 17-0010646
## 5 3 7 1 1 1
## 17-0010664 17-0010667 17-0010669 17-0010671 17-0010676 17-0010690
## 1 2 1 1 1 1
## 17-0010698 17-0010721 17-0010731 17-0010736 17-0010741 17-0010756
## 1 1 1 1 2 1
## 17-0010762 17-0010764 17-0010765 17-0010769 17-0010781 17-0010794
## 1 1 3 1 1 1
## 17-0010798 17-0010803 17-0010805 17-0010812 17-0010814 17-0010826
## 2 1 1 2 2 1
## 17-0010831 17-0010839 17-0010841 17-0010842 17-0010846 17-0010847
## 3 1 1 1 1 1
## 17-0010849 17-0010850 17-0010864 17-0010870 17-0010882 17-0010883
## 1 1 1 4 1 1
## 17-0010888 17-0010892 17-0010893 17-0010896 17-0010902 17-0010917
## 1 1 1 1 1 2
## 17-0010921 17-0010922 17-0010936 17-0010939 17-0010941 17-0010942
## 1 1 2 1 1 1
## 17-0010947 17-0010950 17-0010951 17-0010953 17-0010954 17-0010965
## 1 1 1 1 3 1
## 17-0010967 17-0010968 17-0010971 17-0010974 17-0010977 17-0010982
## 3 1 2 9 1 1
## 17-0010984 17-0010986 17-0010987 17-0010993 17-0010994 17-0011002
## 1 1 1 3 1 1
## 17-0011006 17-0011015 17-0011016 17-0011019 17-0011021 17-0011024
## 1 1 1 1 1 1
## 17-0011028 17-0011030 17-0011031 17-0011033 17-0011034 17-0011042
## 1 1 1 1 1 1
## 17-0011051 17-0011058 17-0011063 17-0011070 17-0011079 17-0011085
## 3 1 3 1 1 1
## 17-0011088 17-0011089 17-0011090 17-0011093 17-0011094 17-0011103
## 1 2 1 1 1 1
## 17-0011106 17-0011111 17-0011112 17-0011114 17-0011115 17-0011120
## 1 1 1 1 1 1
## 17-0011133 17-0011145 17-0011147 17-0011151 17-0011152 17-0011155
## 2 5 2 1 5 2
## 17-0011156 17-0011167 17-0011172 17-0011186 17-0011188 17-0011191
## 1 1 5 1 1 1
## 17-0011196 17-0011201 17-0011202 17-0011204 17-0011210 17-0011213
## 1 1 1 1 1 1
## 17-0011215 17-0011218 17-0011230 17-0011232 17-0011234 17-0011238
## 1 3 1 1 1 3
## 17-0011242 17-0011246 17-0011247 17-0011250 17-0011255 17-0011257
## 1 1 1 2 2 2
## 17-0011258 17-0011261 17-0011293 17-0011294 17-0011295 17-0011298
## 1 1 1 3 1 1
## 17-0011304 17-0011312 17-0011314 17-0011320 17-0011325 17-0011326
## 1 1 1 2 1 2
## 17-0011333 17-0011346 17-0011354 17-0011359 17-0011363 17-0011365
## 1 1 2 1 1 1
## 17-0011368 17-0011378 17-0011388 17-0011399 17-0011405 17-0011407
## 1 2 1 5 1 1
## 17-0011416 17-0011428 17-0011430 17-0011433 17-0011435 17-0011443
## 1 1 5 1 1 1
## 17-0011454 17-0011465 17-0011467 17-0011469 17-0011476 17-0011479
## 1 1 1 2 1 1
## 17-0011486 17-0011487 17-0011491 17-0011497 17-0011499 17-0011502
## 1 1 1 1 2 2
## 17-0011504 17-0011506 17-0011510 17-0011514 17-0011520 17-0011522
## 1 1 1 1 1 1
## 17-0011523 17-0011526 17-0011527 17-0011531 17-0011533 17-0011538
## 1 1 1 1 2 1
## 17-0011541 17-0011554 17-0011555 17-0011556 17-0011572 17-0011573
## 1 1 10 1 1 1
## 17-0011574 17-0011579 17-0011583 17-0011585 17-0011592 17-0011594
## 1 1 1 1 1 1
## 17-0011606 17-0011608 17-0011609 17-0011613 17-0011619 17-0011621
## 1 3 1 3 1 1
## 17-0011624 17-0011647 17-0011652 17-0011658 17-0011670 17-0011675
## 1 1 1 1 1 1
## 17-0011681 17-0011691 17-0011694 17-0011696 17-0011705 17-0011711
## 10 1 2 1 1 1
## 17-0011716 17-0011719 17-0011722 17-0011725 17-0011730 17-0011731
## 2 3 1 1 1 1
## 17-0011736 17-0011737 17-0011740 17-0011744 17-0011754 17-0011755
## 1 1 1 6 3 9
## 17-0011774 17-0011784 17-0011786 17-0011787 17-0011791 17-0011814
## 5 1 1 1 1 1
## 17-0011816 17-0011817 17-0011819 17-0011822 17-0011823 17-0011825
## 3 1 1 1 1 1
## 17-0011829 17-0011835 17-0011839 17-0011846 17-0011855 17-0011858
## 1 1 13 1 3 1
## 17-0011863 17-0011864 17-0011881 17-0011882 17-0011900 17-0011902
## 4 1 1 3 1 2
## 17-0011912 17-0011918 17-0011919 17-0011931 17-0011937 17-0011938
## 1 1 1 1 1 1
## 17-0011940 17-0011962 17-0011970 17-0011971 17-0011972 17-0011981
## 1 1 4 1 1 1
## 17-0011984 17-0011995 17-0012008 17-0012015 17-0012017 17-0012020
## 1 1 1 3 1 1
## 17-0012031 17-0012033 17-0012034 17-0012036 17-0012039 17-0012048
## 1 1 1 1 1 2
## 17-0012051 17-0012060 17-0012064 17-0012071 17-0012078 17-0012083
## 1 1 1 1 1 1
## 17-0012092 17-0012094 17-0012100 17-0012102 17-0012104 17-0012106
## 1 1 1 1 3 2
## 17-0012114 17-0012116 17-0012125 17-0012128 17-0012129 17-0012130
## 1 1 1 1 1 6
## 17-0012131 17-0012134 17-0012137 17-0012138 17-0012143 17-0012146
## 1 2 1 1 1 2
## 17-0012151 17-0012152 17-0012161 17-0012164 17-0012174 17-0012179
## 10 1 1 3 1 1
## 17-0012184 17-0012185 17-0012188 17-0012194 17-0012207 17-0012213
## 5 1 1 5 1 1
## 17-0012217 17-0012220 17-0012229 17-0012240 17-0012249 17-0012267
## 1 2 2 1 1 1
## 17-0012268 17-0012301 17-0012306 17-0012327 17-0012329 17-0012338
## 1 1 1 1 1 1
## 17-0012358 17-0012364 17-0012371 17-0012379 17-0012391 17-0012396
## 1 1 1 1 1 1
## 17-0012408 17-0012416 17-0012417 17-0012423 17-0012429 17-0012430
## 2 3 1 1 10 1
## 17-0012435 17-0012437 17-0012441 17-0012447 17-0012448 17-0012457
## 1 1 1 1 2 1
## 17-0012459 17-0012460 17-0012466 17-0012477 17-0012479 17-0012487
## 2 1 1 2 1 1
## 17-0012492 17-0012494 17-0012506 17-0012514 17-0012517 17-0012540
## 1 2 1 1 1 1
## 17-0012551 17-0012561 17-0012562 17-0012563 17-0012567 17-0012574
## 10 3 3 1 1 1
## 17-0012578 17-0012579 17-0012584 17-0012588 17-0012593 17-0012599
## 1 1 2 2 1 1
## 17-0012600 17-0012601 17-0012617 17-0012622 17-0012627 17-0012632
## 1 1 1 1 3 1
## 17-0012639 17-0012640 17-0012647 17-0012659 17-0012662 17-0012668
## 1 1 1 1 1 1
## 17-0012692 17-0012693 17-0012696 17-0012705 17-0012760 17-0012767
## 1 1 1 1 1 3
## 17-0012773 17-0012780 17-0012781 17-0012787 17-0012788 17-0012797
## 2 1 2 2 1 1
## 17-0012805 17-0012815 17-0012817 17-0012818
## 1 1 1 1# still have a bunch of multiples that shoudl get cleaned out
buildings.fires.small$fire <- ifelse(is.na(buildings.fires.small$Incident.Number), 0, 1)
building.type.fire <- ddply(buildings.fires.small, c('LU'), summarise, count=length(full_street),
fires=sum(fire))
building.type.fire$perc <- building.type.fire$fires / building.type.fire$count
ggplot(building.type.fire, aes(x=LU, y=perc)) + geom_bar(stat='identity')
buildings.fires.small$decade <- 10 * round(buildings.fires.small$YR_BUILT / 10)
building.decade.fire <- ddply(buildings.fires.small, c('decade'), summarise,
count=length(full_street),
fires=sum(fire))
building.decade.fire$perc <- building.decade.fire$fires / building.decade.fire$count
ggplot(building.decade.fire[building.decade.fire$decade!=0, ],
aes(x=decade, y=perc)) + geom_bar(stat='identity')## Warning: Removed 1 rows containing missing values (position_stack).
building.class.fire <- ddply(buildings.fires.small, c('STRUCTURE_CLASS'), summarise,
count=length(full_street),
fires=sum(fire))
building.class.fire$perc <- building.class.fire$fires / building.class.fire$count
ggplot(building.class.fire,
aes(x=STRUCTURE_CLASS, y=perc)) + geom_bar(stat='identity')
building.cnd.fire <- ddply(buildings.fires.small, c('R_OVRALL_CND'), summarise,
count=length(full_street),
fires=sum(fire))
building.cnd.fire$perc <- building.cnd.fire$fires / building.cnd.fire$count
ggplot(building.cnd.fire,
aes(x=R_OVRALL_CND, y=perc)) + geom_bar(stat='identity')
# todo
# viz by type of building (can we compare to types of buildings in the city?)
# small multiples?
# code all the incident types as fires/not fires AND REDO IT ALL
# get property type/age/size/value details and compare fire risk
# to compare:
# size
# value
# if residential - owner occupied
# should probably do all these plots as raw counts too
# use code enforcement data somehow
code.df <- read.csv('cepviolations.csv')
code.df <- code.df[ ,c('Status_DTTM', 'Description', 'StNo', 'StHigh', 'Street', 'Suffix')]
code.df$date <- ymd(gsub('\\s.*', '', code.df$Status_DTTM))
code.df <- code.df[code.df$date < ymd('2017-03-01') & code.df$date >= ymd('2016-11-01'), ]
table(as.character(code.df$Description))##
## Accessible Means of Egress
## 1
## Acts 1956 as Amended
## 2
## Approval of Documents
## 1
## Approved Construction Doc.
## 1
## Automatic Smoke Detection
## 1
## Basic Principles
## 1
## Building Identification - Owner shall to every building a # representing the address.
## 1
## Building or Use of Premise req
## 5
## Certificate of Occupancy
## 4
## Covers & Canopies
## 1
## Door Hardware
## 1
## Door Operations
## 2
## Door operations-Egress doors
## 1
## Elec work w/o per
## 1
## Emergency Escape
## 1
## Emergency Escape & Rescue
## 1
## Emergency escape and rescue
## 1
## Emergency Exit
## 1
## Exit Passageways
## 2
## Exit Signs
## 1
## Exits
## 1
## Exits Maintained
## 1
## Extermination of Insects, Rodents and Skunks - The owner of a dwelling containing two or more dwelling units shall maintain it and its premises free from all rodents, cockroaches and insect infestation and shall be responsible for exterminating them
## 1
## Failed to comply w PRMT Terms
## 11
## Failure clean sidewalk com
## 14
## Failure clear sidewalk - snow
## 1991
## Failure clear sidewalk - snow:
## 136
## Failure to Obtain Permit
## 106
## Failure To Register
## 19
## Failure to secure a Re-Inspect
## 5
## Failure to secure permit
## 6
## Fire Protection & Life Safety
## 1
## Fire Protection Systems
## 2
## Graffiti on building- 1
## 38
## Graffiti on building- 2
## 11
## Guarding of Live parts
## 1
## Guards
## 2
## IEBC
## 1
## Illegal dumping < 1 cubic yd
## 141
## Illegal dumping 1-5 cubic yd.:
## 2
## illegal parking prop owner 1
## 156
## illegal parking prop owner 2
## 91
## Illegal Vending
## 11
## Illumination
## 2
## Improper storage trash: com
## 596
## Improper storage trash: res
## 6340
## Installation
## 1
## Large building recycling- 1
## 2
## Locks and Latches
## 14
## Maint a dumpster wopermit
## 10
## Maint. of Areas Free from Garbage & Rubbish(Common Areas) - In any dwelling, the owner shall be responsible for maintaining in a clean and sanitary condition free of garbage, rubbish, filth all common areas.
## 1
## Maintenance
## 21
## Materials (A) Min. Standards
## 1
## Maximum Height from Floor
## 1
## Means of Egress
## 1
## No Number On A Building
## 9
## No use of premises permit:
## 2
## Non-Emergency Auto Repair
## 4
## Occupying City prop wo permit
## 111
## Overfilling of barrel/dumpster
## 711
## Overgrown Weeds On Property
## 655
## Owners Installation/Maintenance Responsibility - All facilities and equipment which are required by owner including but not limited to water, gas, electrical and heating, shall be installed in accordance with all accepted codes.
## 2
## Owners Responsibility to Maintain Structural Elements - Structural elements shall be maintained free from holes, cracks, loose plaster, or other defects.
## 2
## Periodic Inspections
## 4
## Permits
## 1
## Posting signs wo authority
## 7
## Protection of Adj. Property
## 7
## Protective Railings and Walls - Safe handrail for every stairway
## 2
## Referenced Codes
## 1
## Reg. Access to Roof Areas
## 1
## Removal snow non-res property
## 57
## Removal snow private prop
## 22
## Removal snow private property
## 10
## Required Inspections
## 1
## Retaining Wall
## 1
## Right of Entry
## 9
## Screens for Doors - Owner shall provide screens for all doorways opening directly to the outside from any dwelling unit or rooming unit; shall be tight fitting; equipped with self-closing device except where screen is designed to slide to the side.
## 2
## Screens for Windows - Owner shall provide screens for all windows on the first 4 floors opening directly to the outside; shall be tight fitting; shall cover opening part of window designed to open
## 1
## Securing & Supporting
## 1
## Security Grilles
## 1
## Shared Facilities - Sinks, Toilets, Tubs, showers shared by more than 1 unit or 1 rooming unit shall be cleaned and sanitized once every 24 hrs by owner.
## 1
## Shopping Cart - 1
## 1
## Sign: COB Zoning Article 11-1
## 2
## Sinks, Toilets, Tubs, Showers - Owner shall provide a toilet, a wash basin, bathtub or shower in another room which is not used for living, sleeping, cooking or eating; room must be fitted with a door capable of being closed
## 1
## Site Cleanliness license – VIO
## 2
## Site Cleanliness license – WAR
## 67
## Submittal Documents
## 1
## Testing & Certification
## 14
## Testing and Maintenance
## 1
## Trash illegally dump container
## 13
## Unlawful Continuance
## 1
## Unregistered motor vehicles- 2
## 116
## Unregistered motor vehicles-1
## 71
## Unsafe and Dangerous
## 2
## Unsafe Structure
## 90
## Use of Premises
## 2
## Weathertight Windows
## 2# we have baseline fire numbers
# do properties with any of these violations have higher/lower rates of fire?